Discovering robust protein biomarkers for disease from relative expression reversals in 2-D DIGE data

This study assesses the ability of a novel family of machine learning algorithms to identify changes in relative protein expression levels, measured using 2-D DIGE data, which support accurate class prediction. The analysis was done using a training set of 36 total cellular lysates comprised of six normal and three cancer biological replicates (the remaining are technical replicates) and a validation set of four normal and two cancer samples. Protein samples were separated by 2-D DIGE and expression was quantified using DeCyder-2D Differential Analysis Software. The relative expression reversal (RER) classifier correctly classified 9/9 training biological samples (p<0.022) as estimated using a modified version of leave one out cross validation and 6/6 validation samples. The classification rule involved comparison of expression levels for a single pair of protein spots, tropomyosin isoforms and alpha-enolase, both of which have prior association as potential biomarkers in cancer. The data was also analyzed using algorithms similar to those found in the extended data analysis package of DeCyder software. We propose that by accounting for sources of within- and between-gel variation, RER classifiers applied to 2-D DIGE data provide a useful approach for identifying biomarkers that discriminate among protein samples of interest.     

Frontiers in glycomics; bioinformatics and biomarkers in disease. September 11-13, 2006 Natcher Conference Center, NIH Campus, Bethesda, MD, USA

This is a short summary of a meeting entitled "The Frontiers in Glycomics; Bioinformatics and Biomarkers in Disease" which was jointly organized by the NIH Consortium for Functional Glycomics (CFG), Human Disease Glycomics/Proteome Initiative (HGPI), National Cancer Institute, National Institute of General Medical Sciences, Japan Society for the Promotion of Science and National Center for Research Resources held at the NIH Campus, Bethesda, MD, Natcher Conference Center in September 11-13, 2006.     

Sequence analysis and rule development of predicting protein stability change upon mutation using decision tree model

Understanding the mechanism of the protein stability change is one of the most challenging tasks. Recently, the prediction of protein stability change affected by single point mutations has become an interesting topic in molecular biology. However, it is desirable to further acquire knowledge from large databases to provide new insights into the nature of them. This paper presents an interpretable prediction tree method (named iPTREE-2) that can accurately predict changes of protein stability upon mutations from sequence based information and analyze sequence characteristics from the viewpoint of composition and order. Therefore, iPTREE-2 based on a regression tree algorithm exhibits the ability of finding important factors and developing rules for the purpose of data mining. On a dataset of 1859 different single point mutations from thermodynamic database, ProTherm, iPTREE-2 yields a correlation coefficient of 0.70 between predicted and experimental values. In the task of data mining, detailed analysis of sequences reveals the possibility of the compositional specificity of residues in different ranges of stability change and implies the existence of certain patterns. As building rules, we found that the mutation residues in wild type and in mutant protein play an important role. The present study demonstrates that iPTREE-2 can serve the purpose of predicting protein stability change, especially when one requires more understandable knowledge.     

ProSight Annotator: Complete control and customization of protein entries in UniProt XML files

The effectiveness of any proteomics database search depends on the theoretical candidate information contained in the protein database. Unfortunately, candidate entries from protein databases such as UniProt rarely contain all the post-translational modifications (PTMs), disulfide bonds, or endogenous cleavages of interest to researchers. These omissions can limit discovery of novel and biologically important proteoforms. Conversely, searching for a specific proteoform becomes a computationally difficult task for heavily modified proteins. Both situations require updates to the database through user-annotated entries. Unfortunately, manually creating properly formatted UniProt Extensible Markup Language (XML) files is tedious and prone to errors. ProSight Annotator solves these issues by providing a graphical interface for adding user-defined features to UniProt-formatted XML files for better informed proteoform searches. It can be downloaded from http://prosightannotator.northwestern.edu .     

肠道噬菌体组生物信息学分析方法的研究进展

噬菌体是感染细菌的病毒,广泛存在于各类环境中。由于传统实验研究的局限性及噬菌体基因的特异性,导致对肠道噬菌体的研究很少。随着宏基因组测序技术的发展和各种生物信息分析软件的开发,可以通过噬菌体组学,加深对肠道噬菌体的认识。噬菌体组分析流程主要包括原始数据质量控制和预处理,病毒基因组序列的拼接组装,类病毒颗粒的筛选和系统分类注释以及进化分析和预测相应宿主细菌。本文对噬菌体组分析流程和其中所需要的常用生物信息分析工具和数据库进行详细的介绍,可以为肠道噬菌体研究以及相关的研究人员提供参考。     

Design of a polytopic construct of LACK,TSA and GP63 proteins for the diagnosis of cutaneous leishmaniasis: An in silico strategy

Cutaneous leishmaniasis (CL), which is caused by different species of the genus Leishmania, including L. major, is a significant parasitic disease worldwide. Commercial leishmaniasis diagnostic kits frequently target the entire parasite antigen, although this approach can reduce the specificity of the tests. The present study sought to increase the specificity of antigen detection tests by identifying the B-cell epitopes on the surface of the protozoa and developing an antigenic multiepitope construct to react with the system of B-cell epitopes unique to L. major. More specifically, the linear and conformational B-cell epitopes for three L. major proteins, namely, GP63, LACK, and TSA, were predicted using the ABCprd, IEDB, LBtope, CBTOPE, and DiscoTope servers. The three-dimensional structures of these proteins, as well as of the complete multiepitope, were predicted using the I-TASSER server. The multiepitope structure models were validated by means of Ramachandran plots and the Prosa and Verify3D servers. The multiepitope construct was evaluated using the ProtParam and SOLpro servers. The synthesized multiepitope was then successfully expressed into a pET28a plasmid. The expression was confirmed using SDS-PAGE and dot blot techniques. Moreover, the expressed protein was evaluated by means of Western blotting. A band of approximately 39 kDa was observed by SDS-PAGE. The rGLT-pET-28a showed a high response with the 1:1000 dilution of the anti-His-tag monoclonal antibody by Western blot. The results of this study indicated that the integrated GP63, LACK, and TSA multiepitope antigens of L. major represent a potential target for a novel diagnostic kit for CL.     

3D-QSAR assisted identification of FABP4 inhibitors: An effective scaffold hopping analysis/QSAR evaluation

Following on the recent publication of pharmacologically relevant effects, small molecule inhibitors of adipocyte fatty-acid binding protein 4 (FABP4) have attracted high interest. FABP4 is mainly expressed in macrophages and adipose tissue, where it regulates fatty acid storage and lipolysis, being also an important mediator of inflammation. In this regard, FABP4 recently demonstrated an interesting molecular target for the treatment of type 2 diabetes, other metabolic diseases and some type of cancers. In the past years, hundreds of effective FABP4 inhibitors have been synthesized. In this paper, a quantitative structure-activity relationship (QSAR) model has been produced, in order to predict the bioactivity of FABP4 inhibitors. The methodology has been combined with a scaffold-hopping approach, allowing to identify three new molecules that act as effective inhibitors of this protein. These molecules, synthesized and tested for their FABP4 inhibitor activity, showed IC₅₀ values between 3.70 and 5.59 μM, with a high level of agreement with the predicted values.     

Gene co-expression network analysis for identifying genetic markers in Parkinson's disease - a three-way comparative approach

Parkinson's disease (PD) is a neurodegenerative disorder involving progressive deterioration of dopaminergic neurons. Although few genetic markers for familial PD are known, the etiology of sporadic PD remains poorly understood. Microarray data was analysed for induced pluripotent stem cells (iPSCs) derived from PD patients and mature neuronal cells (mDA) differentiated from these iPSCs. Combining expression and semantic similarity, a highly-correlated PD interactome was constructed that included interactions of established Parkinson's disease marker genes. A novel three-way comparative approach was employed, delineating topologically and functionally important genes. These genes showed involvement in pathways like Parkin-ubiquitin proteosomal system (UPS), immune associated biological processes and apoptosis. Of interest are three genes, eEF1A1, CASK, and PSMD6 that are linked to PARK2 activity in the cell and thereby form attractive candidate genes for understanding PD. Network biology approach delineated in this study can be applied to other neurodegenerative disorders for identification of important genetic regulators.     

Exploring dengue proteome to design an effective epitope-based vaccine against dengue virus

Dengue, a mosquito-borne disease, is caused by four known dengue serotypes. This infection causes a range of symptoms from a mild fever to a sever homorganic fever and death. It is a serious public health problem in subtropical and tropical countries. There is no specific vaccine currently available for clinical use and study on this issue is ongoing. In this study, bioinformatics approaches were used to predict antigenic, immunogenic, non-allergenic, and conserved B and T-cell epitopes as promising targets to design an effective peptide-based vaccine against dengue virus. Molecular docking analysis indicated the deep binding of the identified epitopes in the binding groove of the most popular human MHC I allele (human leukocyte antigens [HLA] A*0201). The final vaccine construct was created by conjugating the B and T-cell identified epitopes using proper linkers and adding an appropriate adjuvant at the N-terminal. The characteristics of the new subunit vaccine demonstrated that the epitope-based vaccine was antigenic, non-toxic, stable, and soluble. Other physicochemical properties of the new designed construct including isoelectric point value, aliphatic index, and grand average of hydropathicity were biologically considerable. Molecular docking of the engineered vaccine with Toll-like receptor 2 (TLR2) model revealed the hydrophobic interaction between the adjuvant and the ligand binding regions in the hydrophobic channel of TLR2. The study results indicated the high potential capability of the new multi-epitope vaccine to induce cellular and humoral immune responses against the dengue virus. Further experimental tests are required to investigate the immune protection capacity of the new vaccine construct in animal models.

Communicated by Ramaswamy H. Sarma     

A database of mutants and effects of site-directed mutagenesis experiments on G protein-coupled receptors

A database system and computer programs for storage and retrieval of information about guanine nucleotide-binding protein (G protein) -coupled receptor mutants and associated biological effects have been developed. Mutation data on the receptors were collected from the literature and a database of mutants and effects of mutations was developed. The G protein-coupled receptor, family A, point mutation database (GRAP) provides detailed information on ligand-binding and signal transduction properties of more than 2130 receptor mutants. The amino acid sequences of receptors for which mutation experiments have been reported were aligned, and from this alignment mutation data may be retrieved. Alternatively, a search form allowing detailed specification of which mutants to retrieve may be used, for example, to search for specific amino acid substitutions, substitutions in specific protein domains or reported biological effects. Furthermore, ligand and bibliographic oriented queries may be performed. GRAP is available on the Internet (URL: http://www-grap.fagmed.uit.no/GRAP/homepage.html ) using the World-Wide Web system. © 1996 Wiley-Liss, Inc.